Image Contrast Enhancement Using Particle Swarm Optimization

Eldho Paul, R. Anand, P. Vivek Karthick, M.E. Paramasivam and P.M. Dinesh

In this paper a new methodology for contrast enhancement using Particle Swarm Optimization (PSO) is proposed. The brightness function of an image is taken as transformation function. The enhancement process is considered as a non-linear optimization problem with tuning the parameters. The parameters of the transformation function are solved or tuned by Particle Swarm Optimization (PSO). The objective of the PSO is to maximize value of fitness criterion in order to enhance the contrast in an image. For measuring objective criterion of enhanced image, the quantitative metrics like PSNR, Entropy and Edge information of the image is considered. The PSO based algorithm is compared with spatial and transform domain techniques like Local contrast stretching (LCS), Histogram equalization (HE), and DWT-SVD. The proposed PSO method yields qualitative and quantitative results compared to other state of art techniques.

Volume 11 | 04-Special Issue

Pages: 1192-1196